Ophthalmology (Eye & Ear Hospital) - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 100
  • Item
    Thumbnail Image
    Recommendations for OCT Angiography Reporting in Retinal Vascular Disease: A Delphi Approach by International Experts.
    Munk, MR ; Kashani, AH ; Tadayoni, R ; Korobelnik, J-F ; Wolf, S ; Pichi, F ; Koh, A ; Ishibazawa, A ; Gaudric, A ; Loewenstein, A ; Lumbroso, B ; Ferrara, D ; Sarraf, D ; Wong, DT ; Skondra, D ; Rodriguez, FJ ; Staurenghi, G ; Pearce, I ; Kim, JE ; Freund, KB ; Parodi, MB ; Waheed, NK ; Rosen, R ; Spaide, RF ; Nakao, S ; Sadda, S ; Vujosevic, S ; Wong, TY ; Murata, T ; Chakravarthy, U ; Ogura, Y ; Huf, W ; Tian, M (Elsevier BV, 2022-09)
    PURPOSE: To develop a consensus nomenclature for reporting OCT angiography (OCTA) findings in retinal vascular disease (e.g., diabetic retinopathy, retinal vein occlusion) by international experts. DESIGN: Delphi-based survey. SUBJECTS, PARTICIPANTS, AND/OR CONTROLS: Twenty-five retinal vascular disease and OCTA imaging experts. METHODS, INTERVENTION, OR TESTING: A Delphi method of consensus development was used, comprising 2 rounds of online questionnaires, followed by a face-to-face meeting conducted virtually. Twenty-five experts in retinal vascular disease and retinal OCTA imaging were selected to constitute the OCTA Nomenclature in Delphi Study Group for retinal vascular disease. The 4 main areas of consensus were: definition of the parameters of "wide-field (WF)" OCTA, measurement of decreased vascular flow on conventional and WF-OCTA, nomenclature of OCTA findings, and OCTA in retinal vascular disease management and staging. The study end point was defined by the degree of consensus for each question: "strong consensus" was defined as ≥85% agreement, "consensus" as 80% to 84%, and "near consensus" as 70% to 79%. MAIN OUTCOME MEASURES: Consensus and near consensus on OCTA nomenclature in retinal vascular disease. RESULTS: A consensus was reached that a meaningful change in percentage of flow on WF-OCTA imaging should be an increase or decrease ≥30% of the absolute imaged area of flow signal and that a "large area" of WF-OCTA reduced flow signal should also be defined as ≥30% of the absolute imaged area. The presence of new vessels and intraretinal microvascular abnormalities, the foveal avascular zone parameters, the presence and amount of "no-flow areas," and the assessment of vessel density in various retinal layers should be added for the staging and classification of diabetic retinopathy. Decreased flow ≥30% of the absolute imaged area should define an ischemic central retinal vein occlusion. Several other items did not meet consensus requirements or were rejected in the final discussion round. CONCLUSIONS: This study provides international consensus recommendations for reporting OCTA findings in retinal vascular disease, which may help to improve the interpretability and description in clinic and clinical trials. Further validation in these settings is warranted and ongoing. Efforts are continuing to address unresolved questions.
  • Item
    Thumbnail Image
    Retinal neural dysfunction in diabetes revealed with handheld chromatic pupillometry.
    Tan, T-E ; Finkelstein, MT ; Tan, GSW ; Tan, ACS ; Chan, CM ; Mathur, R ; Wong, EYM ; Cheung, CMG ; Wong, TY ; Milea, D ; Najjar, RP (Wiley, 2022-09)
    BACKGROUND: To evaluate the ability of handheld chromatic pupillometry to reveal and localise retinal neural dysfunction in diabetic patients with and without diabetic retinopathy (DR). METHODS: This cross-sectional study included 82 diabetics (DM) and 93 controls (60.4 ± 8.4 years, 44.1% males). DM patients included those without (n = 25, 64.7 ± 6.3 years, 44.0% males) and with DR (n = 57, 60.3 ± 8.5 years, 64.9% males). Changes in horizontal pupil radius in response to blue (469 nm) and red (640 nm) light stimuli were assessed monocularly, in clinics, using a custom-built handheld pupillometer. Pupillometric parameters (phasic constriction amplitudes [predominantly from the outer retina], maximal constriction amplitudes [from the inner and outer retina] and post-illumination pupillary responses [PIPRs; predominantly from the inner retina]) were extracted from baseline-adjusted pupillary light response traces and compared between controls, DM without DR, and DR. Net PIPR was defined as the difference between blue and red PIPRs. RESULTS: Phasic constriction amplitudes to blue and red lights were decreased in DR compared to controls (p < 0.001; p < 0.001). Maximal constriction amplitudes to blue and red lights were decreased in DR compared to DM without DR (p < 0.001; p = 0.02), and in DM without DR compared to controls (p < 0.001; p = 0.005). Net PIPR was decreased in both DR and DM without DR compared to controls (p = 0.02; p = 0.03), suggesting a wavelength-dependent (and hence retinal) pupillometric dysfunction in diabetic patients with or without DR. CONCLUSIONS: Handheld chromatic pupillometry can reveal retinal neural dysfunction in diabetes, even without DR. Patients with DM but no DR displayed primarily inner retinal dysfunction, while patients with DR showed both inner and outer retinal dysfunction.
  • Item
    Thumbnail Image
    Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective
    Gunasekeran, DVV ; Zheng, F ; Lim, GYS ; Chong, CCY ; Zhang, S ; Ng, WY ; Keel, S ; Xiang, Y ; Park, KH ; Park, SJ ; Chandra, A ; Wu, L ; Campbel, JP ; Lee, AYY ; Keane, PAA ; Denniston, A ; Lam, DSC ; Fung, ATT ; Chan, PRV ; Sadda, SR ; Loewenstein, A ; Grzybowski, A ; Fong, KCS ; Wu, W-C ; Bachmann, LM ; Zhang, X ; Yam, JC ; Cheung, CYY ; Pongsachareonnont, P ; Ruamviboonsuk, P ; Raman, R ; Sakamoto, T ; Habash, R ; Girard, M ; Milea, D ; Ang, M ; Tan, GSW ; Schmetterer, L ; Cheng, C-Y ; Lamoureux, E ; Lin, H ; van Wijngaarden, P ; Wong, TYY ; Ting, DSW (FRONTIERS MEDIA SA, 2022-10-13)
    BACKGROUND: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83. CONCLUSION: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.
  • Item
    Thumbnail Image
    System-wide vitreous proteome dissection reveals impaired sheddase activity in diabetic retinopathy.
    Alli-Shaik, A ; Qiu, B ; Lai, SL ; Cheung, N ; Tan, G ; Neo, SP ; Tan, A ; Cheung, CMG ; Hong, W ; Wong, TY ; Wang, X ; Gunaratne, J (Ivyspring International Publisher, 2022)
    Rationale: Diabetic retinopathy (DR) is a major complication of diabetes mellitus causing significant vision loss. DR is a multifactorial disease involving changes in retinal microvasculature and neuronal layers, and aberrations in vascular endothelial growth factors (VEGF) and inflammatory pathways. Despite the success of anti-VEGF therapy, many DR patients do not respond well to the treatment, emphasizing the involvement of other molecular players in neuronal and vascular aberrations in DR. Methods: We employed advanced mass spectrometry-based proteome profiling to obtain a global snapshot of altered protein abundances in vitreous humor from patients with proliferative DR (PDR) in comparison to individuals with epiretinal membrane without active DR or other retinal vascular complications. Global proteome correlation map and protein-protein interaction networks were used to probe into the functional inclination of proteins and aberrated molecular networks in PDR vitreous. In addition, peptide-centric analysis of the proteome data was carried out to identify proteolytic processing, primarily ectodomain shedding events in PDR vitreous. Functional validation experiments were performed using preclinical models of ocular angiogenesis. Results: The vitreous proteome landscape revealed distinct dysregulations in several metabolic, signaling, and immune networks in PDR. Systematic analysis of altered proteins uncovered specific impairment in ectodomain shedding of several transmembrane proteins playing critical roles in neurodegeneration and angiogenesis, pointing to defects in their regulating sheddases, particularly ADAM10, which emerged as the predominant sheddase. We confirmed that ADAM10 protease activity was reduced in animal models of ocular angiogenesis and established that activation of ADAM10 can suppress endothelial cell activation and angiogenesis. Furthermore, we identified the impaired ADAM10-AXL axis as a driver of retinal angiogenesis. Conclusion: We demonstrate restoration of aberrant ectodomain shedding as an effective strategy for treating PDR and propose ADAM10 as an attractive therapeutic target. In all, our study uncovered impaired ectodomain shedding as a prominent feature of PDR, opening new possibilities for advancement in the DR therapeutic space.
  • Item
    Thumbnail Image
    Analysis of clinically relevant variants from ancestrally diverse Asian genomes.
    Chan, SH ; Bylstra, Y ; Teo, JX ; Kuan, JL ; Bertin, N ; Gonzalez-Porta, M ; Hebrard, M ; Tirado-Magallanes, R ; Tan, JHJ ; Jeyakani, J ; Li, Z ; Chai, JF ; Chong, YS ; Davila, S ; Goh, LL ; Lee, ES ; Wong, E ; Wong, TY ; SG10K_Health Consortium, ; Prabhakar, S ; Liu, J ; Cheng, C-Y ; Eisenhaber, B ; Karnani, N ; Leong, KP ; Sim, X ; Yeo, KK ; Chambers, JC ; Tai, E-S ; Tan, P ; Jamuar, SS ; Ngeow, J ; Lim, WK (Springer Science and Business Media LLC, 2022-11-05)
    Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.
  • Item
    Thumbnail Image
    Classification of diabetic retinopathy: Past, present and future.
    Yang, Z ; Tan, T-E ; Shao, Y ; Wong, TY ; Li, X (Frontiers Media SA, 2022)
    Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide. Since DR was first recognized as an important complication of diabetes, there have been many attempts to accurately classify the severity and stages of disease. These historical classification systems evolved as understanding of disease pathophysiology improved, methods of imaging and assessing DR changed, and effective treatments were developed. Current DR classification systems are effective, and have been the basis of major research trials and clinical management guidelines for decades. However, with further new developments such as recognition of diabetic retinal neurodegeneration, new imaging platforms such as optical coherence tomography and ultra wide-field retinal imaging, artificial intelligence and new treatments, our current classification systems have significant limitations that need to be addressed. In this paper, we provide a historical review of different classification systems for DR, and discuss the limitations of our current classification systems in the context of new developments. We also review the implications of new developments in the field, to see how they might feature in a future, updated classification.
  • Item
    Thumbnail Image
    Diabetic retinopathy: Looking forward to 2030.
    Tan, T-E ; Wong, TY (Frontiers Media SA, 2022)
    Diabetic retinopathy (DR) is the major ocular complication of diabetes mellitus, and is a problem with significant global health impact. Major advances in diagnostics, technology and treatment have already revolutionized how we manage DR in the early part of the 21st century. For example, the accessibility of imaging with optical coherence tomography, and the development of anti-vascular endothelial growth factor (VEGF) treatment are just some of the landmark developments that have shaped the DR landscape over the last few decades. Yet, there are still more exciting advances being made. Looking forward to 2030, many of these ongoing developments are likely to further transform the field. First, epidemiologic projections show that the global burden of DR is not only increasing, but also shifting from high-income countries towards middle- and low-income areas. Second, better understanding of disease pathophysiology is placing greater emphasis on retinal neural dysfunction and non-vascular aspects of diabetic retinal disease. Third, a wealth of information is becoming available from newer imaging modalities such as widefield imaging systems and optical coherence tomography angiography. Fourth, artificial intelligence for screening, diagnosis and prognostication of DR will become increasingly accessible and important. Fifth, new pharmacologic agents targeting other non-VEGF-driven pathways, and novel therapeutic strategies such as gene therapy are being developed for DR. Finally, the classification system for diabetic retinal disease will need to be continually updated to keep pace with new developments. In this article, we discuss these major trends in DR that we expect to see in 2030 and beyond.
  • Item
    Thumbnail Image
    A saturated map of common genetic variants associated with human height
    Yengo, L ; Vedantam, S ; Marouli, E ; Sidorenko, J ; Bartell, E ; Sakaue, S ; Graff, M ; Eliasen, AU ; Jiang, Y ; Raghavan, S ; Miao, J ; Arias, JD ; Graham, SE ; Mukamel, RE ; Spracklen, CN ; Yin, X ; Chen, S-H ; Ferreira, T ; Highland, HH ; Ji, Y ; Karaderi, T ; Lin, K ; Lull, K ; Malden, DE ; Medina-Gomez, C ; Machado, M ; Moore, A ; Rueger, S ; Sim, X ; Vrieze, S ; Ahluwalia, TS ; Akiyama, M ; Allison, MA ; Alvarez, M ; Andersen, MK ; Ani, A ; Appadurai, V ; Arbeeva, L ; Bhaskar, S ; Bielak, LF ; Bollepalli, S ; Bonnycastle, LL ; Bork-Jensen, J ; Bradfield, JP ; Bradford, Y ; Braund, PS ; Brody, JA ; Burgdorf, KS ; Cade, BE ; Cai, H ; Cai, Q ; Campbell, A ; Canadas-Garre, M ; Catamo, E ; Chai, J-F ; Chai, X ; Chang, L-C ; Chang, Y-C ; Chen, C-H ; Chesi, A ; Choi, SH ; Chung, R-H ; Cocca, M ; Concas, MP ; Couture, C ; Cuellar-Partida, G ; Danning, R ; Daw, EW ; Degenhard, F ; Delgado, GE ; Delitala, A ; Demirkan, A ; Deng, X ; Devineni, P ; Dietl, A ; Dimitriou, M ; Dimitrov, L ; Dorajoo, R ; Ekici, AB ; Engmann, JE ; Fairhurst-Hunter, Z ; Farmaki, A-E ; Faul, JD ; Fernandez-Lopez, J-C ; Forer, L ; Francescatto, M ; Freitag-Wolf, S ; Fuchsberger, C ; Galesloot, TE ; Gao, Y ; Gao, Z ; Geller, F ; Giannakopoulou, O ; Giulianini, F ; Gjesing, AP ; Goel, A ; Gordon, SD ; Gorski, M ; Grove, J ; Guo, X ; Gustafsson, S ; Haessler, J ; Hansen, TF ; Havulinna, AS ; Haworth, SJ ; He, J ; Heard-Costa, N ; Hebbar, P ; Hindy, G ; Ho, Y-LA ; Hofer, E ; Holliday, E ; Horn, K ; Hornsby, WE ; Hottenga, J-J ; Huang, H ; Huang, J ; Huerta-Chagoya, A ; Huffman, JE ; Hung, Y-J ; Huo, S ; Hwang, MY ; Iha, H ; Ikeda, DD ; Isono, M ; Jackson, AU ; Jager, S ; Jansen, IE ; Johansson, I ; Jonas, JB ; Jonsson, A ; Jorgensen, T ; Kalafati, I-P ; Kanai, M ; Kanoni, S ; Karhus, LL ; Kasturiratne, A ; Katsuya, T ; Kawaguchi, T ; Kember, RL ; Kentistou, KA ; Kim, H-N ; Kim, YJ ; Kleber, ME ; Knol, MJ ; Kurbasic, A ; Lauzon, M ; Le, P ; Lea, R ; Lee, J-Y ; Leonard, HL ; Li, SA ; Li, X ; Li, X ; Liang, J ; Lin, H ; Lin, S-Y ; Liu, J ; Liu, X ; Lo, KS ; Long, J ; Lores-Motta, L ; Luan, J ; Lyssenko, V ; Lyytikainen, L-P ; Mahajan, A ; Mamakou, V ; Mangino, M ; Manichaikul, A ; Marten, J ; Mattheisen, M ; Mavarani, L ; McDaid, AF ; Meidtner, K ; Melendez, TL ; Mercader, JM ; Milaneschi, Y ; Miller, JE ; Millwood, IY ; Mishra, PP ; Mitchell, RE ; Mollehave, LT ; Morgan, A ; Mucha, S ; Munz, M ; Nakatochi, M ; Nelson, CP ; Nethander, M ; Nho, CW ; Nielsen, AA ; Nolte, IM ; Nongmaithem, SS ; Noordam, R ; Ntalla, I ; Nutile, T ; Pandit, A ; Christofidou, P ; Parna, K ; Pauper, M ; Petersen, ERB ; Petersen, L ; Pitkanen, N ; Polasek, O ; Poveda, A ; Preuss, MH ; Pyarajan, S ; Raffield, LM ; Rakugi, H ; Ramirez, J ; Rasheed, A ; Raven, D ; Rayner, NW ; Riveros, C ; Rohde, R ; Ruggiero, D ; Ruotsalainen, SE ; Ryan, KA ; Sabater-Lleal, M ; Saxena, R ; Scholz, M ; Sendamarai, A ; Shen, B ; Shi, J ; Shin, JH ; Sidore, C ; Sitlani, CM ; Slieker, RKC ; Smit, RAJ ; Smith, A ; Smith, JA ; Smyth, LJ ; Southam, LE ; Steinthorsdottir, V ; Sun, L ; Takeuchi, F ; Tallapragada, D ; Taylor, KD ; Tayo, BO ; Tcheandjieu, C ; Terzikhan, N ; Tesolin, P ; Teumer, A ; Theusch, E ; Thompson, DJ ; Thorleifsson, G ; Timmers, PRHJ ; Trompet, S ; Turman, C ; Vaccargiu, S ; van der Laan, SW ; van der Most, PJ ; van Klinken, JB ; van Setten, J ; Verma, SS ; Verweij, N ; Veturi, Y ; Wang, CA ; Wang, C ; Wang, L ; Wang, Z ; Warren, HR ; Wei, WB ; Wickremasinghe, AR ; Wielscher, M ; Wiggins, KL ; Winsvold, BS ; Wong, A ; Wu, Y ; Wuttke, M ; Xia, R ; Xie, T ; Yamamoto, K ; Yang, J ; Yao, J ; Young, H ; Yousri, NA ; Yu, L ; Zeng, L ; Zhang, W ; Zhang, X ; Zhao, J-H ; Zhao, W ; Zhou, W ; Zimmermann, ME ; Zoledziewska, M ; Adair, LS ; Adams, HHH ; Aguilar-Salinas, CA ; Al-Mulla, F ; Arnett, DK ; Asselbergs, FW ; Asvold, BO ; Attia, J ; Banas, B ; Bandinelli, S ; Bennett, DA ; Bergler, T ; Bharadwaj, D ; Biino, G ; Bisgaard, H ; Boerwinkle, E ; Boger, CA ; Bonnelykke, K ; Boomsma, D ; Borglum, AD ; Borja, JB ; Bouchard, C ; Bowden, DW ; Brandslund, I ; Brumpton, B ; Buring, JE ; Caulfield, MJ ; Chambers, JC ; Chandak, GR ; Chanock, SJ ; Chaturvedi, N ; Chen, Y-DI ; Chen, Z ; Cheng, C-Y ; Christophersen, IE ; Ciullo, M ; Cole, JW ; Collins, FS ; Cooper, RS ; Cruz, M ; Cucca, F ; Cupples, LA ; Cutler, MJ ; Damrauer, SM ; Dantoft, TM ; de Borst, GJ ; de Groot, LCPGM ; De Jager, PL ; de Kleijn, DP ; de Silva, HJ ; Dedoussis, G ; den Hollander, A ; Du, S ; Easton, DF ; Elders, PJM ; Eliassen, AH ; Ellinor, PT ; Elmstahl, S ; Erdmann, J ; Evans, MK ; Fatkin, D ; Feenstra, B ; Feitosa, MF ; Ferrucci, L ; Ford, I ; Fornage, M ; Franke, A ; Franks, PW ; Freedman, B ; Gasparini, P ; Gieger, C ; Girotto, G ; Goddard, ME ; Golightly, YM ; Gonzalez-Villalpando, C ; Gordon-Larsen, P ; Grallert, H ; Grant, SFA ; Grarup, N ; Griffiths, L ; Gudnason, V ; Haiman, C ; Hakonarson, H ; Hansen, T ; Hartman, CA ; Hattersley, AT ; Hayward, C ; Heckbert, SR ; Heng, C-K ; Hengstenberg, C ; Hewitt, AW ; Hishigaki, H ; Hoyng, CB ; Huang, PL ; Huang, W ; Hunt, SC ; Hveem, K ; Hypponen, E ; Iacono, WG ; Ichihara, S ; Ikram, MA ; Isasi, CR ; Jackson, RD ; Jarvelin, M-R ; Jin, Z-B ; Jockel, K-H ; Joshi, PK ; Jousilahti, P ; Jukema, JW ; Kahonen, M ; Kamatani, Y ; Kang, KD ; Kaprio, J ; Kardia, SLR ; Karpe, F ; Kato, N ; Kee, F ; Kessler, T ; Khera, A ; Khor, CC ; Kiemeney, LALM ; Kim, B-J ; Kim, EK ; Kim, H-L ; Kirchhof, P ; Kivimaki, M ; Koh, W-P ; Koistinen, HA ; Kolovou, GD ; Kooner, JS ; Kooperberg, C ; Kottgen, A ; Kovacs, P ; Kraaijeveld, A ; Kraft, P ; Krauss, RM ; Kumari, M ; Kutalik, Z ; Laakso, M ; Lange, LA ; Langenberg, C ; Launer, LJ ; Le Marchand, L ; Lee, H ; Lee, NR ; Lehtimaki, T ; Li, H ; Li, L ; Lieb, W ; Lin, X ; Lind, L ; Linneberg, A ; Liu, C-T ; Liu, J ; Loeffler, M ; London, B ; Lubitz, SA ; Lye, SJ ; Mackey, DA ; Magi, R ; Magnusson, PKE ; Marcus, GM ; Vidal, PM ; Martin, NG ; Marz, W ; Matsuda, F ; McGarrah, RW ; McGue, M ; McKnight, AJ ; Medland, SE ; Mellstrom, D ; Metspalu, A ; Mitchell, BD ; Mitchell, P ; Mook-Kanamori, DO ; Morris, AD ; Mucci, LA ; Munroe, PB ; Nalls, MA ; Nazarian, S ; Nelson, AE ; Neville, MJ ; Newton-Cheh, C ; Nielsen, CS ; Nothen, MM ; Ohlsson, C ; Oldehinkel, AJ ; Orozco, L ; Pahkala, K ; Pajukanta, P ; Palmer, CNA ; Parra, EJ ; Pattaro, C ; Pedersen, O ; Pennell, CE ; Penninx, BWJH ; Perusse, L ; Peters, A ; Peyser, PA ; Porteous, DJ ; Posthuma, D ; Power, C ; Pramstaller, PP ; Province, MA ; Qi, Q ; Qu, J ; Rader, DJ ; Raitakari, OT ; Ralhan, S ; Rallidis, LS ; Rao, DC ; Redline, S ; Reilly, DF ; Reiner, AP ; Rhee, SY ; Ridker, PM ; Rienstra, M ; Ripatti, S ; Ritchie, MD ; Roden, DM ; Rosendaal, FR ; Rotter, J ; Rudan, I ; Rutters, F ; Sabanayagam, C ; Saleheen, D ; Salomaa, V ; Samani, NJ ; Sanghera, DK ; Sattar, N ; Schmidt, B ; Schmidt, H ; Schmidt, R ; Schulze, MB ; Schunkert, H ; Scott, LJ ; Scott, RJ ; Sever, P ; Shiroma, EJ ; Shoemaker, MB ; Shu, X-O ; Simonsick, EM ; Sims, M ; Singh, JR ; Singleton, AB ; Sinner, MF ; Smith, JG ; Snieder, H ; Spector, TD ; Stampfer, MJ ; Stark, KJ ; Strachan, DP ; t' Hart, LM ; Tabara, Y ; Tang, H ; Tardif, J-C ; Thanaraj, TA ; Timpson, NJ ; Tonjes, A ; Tremblay, A ; Tuomi, T ; Tuomilehto, J ; Tusie-Luna, M-T ; Uitterlinden, AG ; van Dam, RM ; van der Harst, P ; Van der Velde, N ; van Duijn, CM ; van Schoor, NM ; Vitart, V ; Volker, U ; Vollenweider, P ; Volzke, H ; Wacher-Rodarte, NH ; Walker, M ; Wang, YX ; Wareham, NJ ; Watanabe, RM ; Watkins, H ; Weir, DR ; Werge, TM ; Widen, E ; Wilkens, LR ; Willemsen, G ; Willett, WC ; Wilson, JF ; Wong, T-Y ; Woo, J-T ; Wright, AF ; Wu, J-Y ; Xu, H ; Yajnik, CS ; Yokota, M ; Yuan, J-M ; Zeggini, E ; Zemel, BS ; Zheng, W ; Zhu, X ; Zmuda, JM ; Zonderman, AB ; Zwart, J-A ; Chasman, D ; Cho, YS ; Heid, IM ; McCarthy, M ; Ng, MCY ; O'Donnell, CJ ; Rivadeneira, F ; Thorsteinsdottir, U ; Sun, Y ; Tai, ES ; Boehnke, M ; Deloukas, P ; Justice, AE ; Lindgren, CM ; Loos, RJF ; Mohlke, KL ; North, KE ; Stefansson, K ; Walters, RG ; Winkler, TW ; Young, KL ; Loh, P-R ; Yang, J ; Esko, T ; Assimes, TL ; Auton, A ; Abecasis, GR ; Willer, CJ ; Locke, AE ; Berndt, S ; Lettre, G ; Frayling, TM ; Okada, Y ; Wood, AR ; Visscher, PM ; Hirschhorn, JN (NATURE PORTFOLIO, 2022-10-27)
    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
  • Item
    Thumbnail Image
    Relationships between Lipid-Related Metabolites and Age-Related Macular Degeneration Vary with Complement Genotype.
    Sim, RZH ; Tham, Y-C ; Betzler, BK ; Zhou, L ; Wang, X ; Sabanayagam, C ; Cheung, GCM ; Wong, TY ; Cheng, C-Y ; Nusinovici, S (Elsevier BV, 2022-12)
    OBJECTIVE: Lipid dysregulation and complement system (CS) activation are 2 important pathophysiology pathways for age-related macular degeneration (AMD). We hypothesized that the relationship between lipids and AMD may also differ according to CS genotype profile. Thus, the objective was to investigate the relationships between lipid-related metabolites and AMD according to CS genotypes. DESIGN: Population-based cross-sectional study. PARTICIPANTS: A total of 6947 participants from Singapore Epidemiology of Eye Diseases study with complete relevant data were included. METHODS: We investigated a total of 32 blood lipid-related metabolites from nuclear magnetic resonance metabolomics data including lipoproteins and their subclasses, cholesterols, glycerides, and phospholipids, as well as 4 CS single nucleotide polymorphisms (SNPs): rs10922109 (complement factor H), rs10033900 (complement factor I), rs116503776 (C2-CFB-SKIV2L), and rs2230199 (C3). We first investigated the associations between AMD and the 32 lipid-related metabolites using multivariable logistic regression models. Then, to investigate whether the effect of lipid-related metabolites on AMD differ according to the CS SNPs, we tested the possible interactions between the CS SNPs and the lipid-related metabolites. MAIN OUTCOME MEASURES: Age-related macular degeneration was defined using the Wisconsin grading system. RESULTS: Among the 6947 participants, the prevalence of AMD was 6.1%, and the mean age was 58.3 years. First, higher levels of cholesterol in high-density lipoprotein (HDL) and medium and large HDL particles were associated with an increased risk of AMD, and higher levels of serum total triglycerides (TG) and several very-low-density lipoprotein subclass particles were associated with a decreased risk of AMD. Second, these lipids had significant interaction effects on AMD with 2 CS SNPs: rs2230199 and rs116503776 (after correction for multiple testing). For rs2230199, in individuals without risk allele, higher total cholesterol in HDL2 was associated with an increased AMD risk (odds ratio [OR] per standard deviation increase, 1.20; 95% confidence interval (CI), 1.06-1.37; P = 0.005), whereas, in individuals with at least 1 risk allele, higher levels of these particles were associated with a decreased AMD risk (OR, 0.69; 95% CI, 0.45-1.05; P = 0.079). Conversely, for rs116503776, in individuals without risk allele, higher serum total TG were associated with a decreased AMD risk (OR, 0.84; 95% CI, 0.74-0.95; P = 0.005), whereas, in individuals with 2 risk alleles, higher levels of these particles were associated with an increased risk of AMD (OR, 2.3, 95% CI, 0.99-5.39, P = 0.054). CONCLUSIONS: Lipid-related metabolites exhibit opposite directions of effects on AMD according to CS genotypes. This indicates that lipid metabolism and CS may have synergistic interplay in the AMD pathogenesis.
  • Item
    Thumbnail Image
    HTRA1 Regulates Subclinical Inflammation and Activates Proangiogenic Response in the Retina and Choroid.
    Ahamed, W ; Yu, RMC ; Pan, Y ; Iwata, T ; Barathi, VA ; Wey, YS ; Tun, SBB ; Qiu, B ; Tan, A ; Wang, X ; Cheung, CMG ; Wong, TY ; Yanagi, Y (MDPI AG, 2022-09-06)
    High-temperature requirement A1 (HtrA1) has been identified as a disease-susceptibility gene for age-related macular degeneration (AMD) including polypoidal choroidal neovasculopathy (PCV). We characterized the underlying phenotypic changes of transgenic (Tg) mice expressing ubiquitous CAG promoter (CAG-HtrA1 Tg). In vivo imaging modalities and histopathology were performed to investigate the possible neovascularization, drusen formation, and infiltration of macrophages. Subretinal white material deposition and scattered white-yellowish retinal foci were detected on CFP [(Tg—33% (20/60) and wild-type (WT)—7% (1/15), p < 0.05]. In 40% (4/10) of the CAG-HtrA1 Tg retina, ICGA showed punctate hyperfluorescent spots. There was no leakage on FFA and OCTA failed to confirm vascular flow signals from the subretinal materials. Increased macrophages and RPE cell migrations were noted from histopathological sections. Monocyte subpopulations were increased in peripheral blood in the CAG-HtrA1 Tg mice (p < 0.05). Laser induced CNV in the CAG-HtrA1 Tg mice and showed increased leakage from CNV compared to WT mice (p < 0.05). Finally, choroidal explants of the old CAG-HtrA1 Tg mice demonstrated an increased area of sprouting (p < 0.05). Signs of subclinical inflammation was observed in CAG-HtrA1 Tg mice. Such subclinical inflammation may have resulted in increased RPE cell activation and angiogenic potential.